Modelling the spatio-temporal risk of measles outbreaks and options for their control in Kenya

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Reference Number: 
GMVMod002
Type of project: 
Modelling
Description: 

Background:

The measles control programme in Kenya is considered to be at it end phase. There has been long-term high level coverage of measles containing vaccine (MCV) at 9m reaching around 90% in 2010-12. Supplementary immunization activities (SIAs) are undertaken periodically (last done in 2016) to reduce the build-up of susceptibles in the age range 9m to 14 years. However, sporadic outbreaks continue, and data suggests vaccine uptake of MCV dose 1 has decreased over the last 5 years (WHO & UNICEF 2017, Manakongtreecheep & Davis 2017). A second dose of MCV was introduced in 2013 at 18months of age, but coverage is only at around 35%, and there is little confidence that this can easily be improved. There is national case-based surveillance, with follow up, through IgM serology from cases of rash illness. There is a need for studies to explore the possible reasons for continued outbreaks and to predict the implications of vaccine coverage at the current level for dose 1 (around 85%) on measles incidence, and the optimal interval and age-range for SIAs.

The project aims to:

  1. Develop a simulation model with spatial heterogeneity in transmission, population density and vaccine uptake
  2. Develop a risk map for measles outbreaks across the country
  3. Provide evidence on control options and recommendations on future data needs

Methods/Study design:

Data will be collated on vaccine coverage for MCV 1 and 2, and laboratory confirmed measles cases, by county across Kenya. A county-based distribution map of population density, measles case rates, and vaccine coverage will be made (Brownwright et al 2017). A spatially explicit simulation model will be developed (Grenfell et al 2001) incorporating these elements and parameters inferred against temporal-spatial case data. Vaccination policy changes will be simulated that distribute vaccine (a) only to low coverage counties (b) nationally or (c) through periodic SIAs (May & Anderson 1984).

The outputs will be:

  1. Risk map for outbreaks of measles across the country with now change in current vaccination or following implementation of a range of policy options
  2. Provision of evidence to the Kenya National Technical Advisory Group (KenNITAG)
  3. Develop in-country skills in predictive modelling of infectious disease

Role of /links with National / Local Public-Health Organisation:
(including access to data, sources of samples, role in defining question and potential impact on policy)

  • These ideas arose from discussions with the Director of the National Vaccine and Immunization Programme – see meeting notes

References:

  1. Brownwright, TK, Dodson, ZM & van Panhuis WG (2017) Spatial clustering of measles vaccination coverage among children in sub-Saharan Africa. BMC Public Health, 17 957
  2. Grenfell, BT, Bjørnstad, ON & Kappey J (2001) Travelling waves and spatial hierarchies in measles epidemics. Nature 414 716-723
  3. Manakongtreecheep, K & Davis, R 2017 A review of measles control in Kenya, with focus on recent innovations. Pan. African Med. J. 27 (Suppl 3) 15.
  4. May, RM & Anderson, RM (1984) Spatial heterogeneity and the design of immunization programs. Math. Biosci. 72, 83–111.
  5. WHO and UNICEF estimates of national immunization coverage (2017) - www.who.int/immunization/monitoring_surveillance/data/ken.pdf
Status: 
Active